Huntag can perform any kind of supervised sequential sentence tagging tasks. It has been used for NP chunking, Named Entity Recognition, and clause chunking. The flexibility of Huntag comes from the fact that it will generate any kind of features from the input data given the appropriate python functions. Several dozens of features used regularly in NLP tasks are already implemented in the file, however the user is encouraged to add any number of her own. Once the desired features are implemented, a data set and a configuration file containing the list of feature functions to be used are all Huntag needs to perform training and tagging. hunner is huntag's instantiation for Named Entity Recognition.

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